rename pkg --> talweg

[talweg.git] / talweg / R / computeForecast.R

diff --git a/talweg/R/computeForecast.R b/talweg/R/computeForecast.R
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+#' Compute forecast
+#'
+#' Predict time-series curves for the selected days indices (lines in data).
+#'
+#' @param data Dataset, object of type \code{Data} output of \code{getData}
+#' @param indices Days indices where to forecast (the day after)
+#' @param forecaster Name of the main forcaster
+#' \itemize{
+#'   \item Persistence : use values of last (similar, next) day
+#'   \item Neighbors : use values from the k closest neighbors' tomorrows
+#'   \item Average : global average of all the (similar) "tomorrow of past"
+#'   \item Zero : just output 0 (benchmarking purpose)
+#' }
+#' @param pjump How to predict the jump at the interface between two days ?
+#' \itemize{
+#'   \item Persistence : use last (similar) day values
+#'   \item Neighbors: re-use the weights optimized in corresponding forecaster
+#'   \item Zero: just output 0 (no adjustment)
+#' }
+#' @param memory Data depth (in days) to be used for prediction
+#' @param horizon Number of time steps to predict
+#' @param ... Additional parameters for the forecasting models
+#'
+#' @return An object of class Forecast
+#'
+#' @examples
+#' ts_data = system.file("extdata","pm10_mesures_H_loc.csv",package="talweg")
+#' exo_data = system.file("extdata","meteo_extra_noNAs.csv",package="talweg")
+#' data = getData(ts_data, exo_data, input_tz = "Europe/Paris",
+#'   working_tz="Europe/Paris", predict_at=7)
+#' pred = computeForecast(data, 2200:2230, "Persistence", "Persistence", 500, 12)
+#' \dontrun{#Sketch for real-time mode:
+#' data = new("Data", ...)
+#' forecaster = new(..., data=data)
+#' repeat {
+#'   data$append(some_new_data)
+#'   pred = forecaster$predict(data$getSize(), ...)
+#'   #do_something_with_pred
+#' }}
+#' @export
+computeForecast = function(data, indices, forecaster, pjump,
+       memory=Inf, horizon=data$getStdHorizon(), ...)
+{
+       # (basic) Arguments sanity checks
+       horizon = as.integer(horizon)[1]
+       if (horizon<=0 || horizon>length(data$getCenteredSerie(2)))
+               stop("Horizon too short or too long")
+       integer_indices = sapply(indices, function(i) dateIndexToInteger(i,data))
+       if (any(integer_indices<=0 | integer_indices>data$getSize()))
+               stop("Indices out of range")
+       if (!is.character(forecaster) || !is.character(pjump))
+               stop("forecaster (name) and pjump (function) should be of class character")
+
+       pred = Forecast$new( sapply(indices, function(i) integerIndexToDate(i,data)) )
+       forecaster_class_name = getFromNamespace(paste(forecaster,"Forecaster",sep=""), "talweg")
+       forecaster = forecaster_class_name$new( #.pjump =
+               getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg"))
+       for (today in integer_indices)
+       {
+               pred$append(
+                       new_serie = forecaster$predictSerie(data, today, memory, horizon, ...),
+                       new_params = forecaster$getParameters(),
+                       new_index_in_data = today
+               )
+       }
+       pred
+}